A reactive adaptive memory metaheuristic for solving HFFVRP

Abstract

Product distribution is one of the most important problems in supply chain management. The heterogeneous fixed fleet vehicle routing problem (HFFVRP) is a variant of VRP that aims to determine the routes for a fleet of vehicles while satisfying demand and minimizing cost. The fleet composition is fixed and it consists of various types of vehicles. These vehicles differ according to their variable cost. In this paper, a reactive adaptive memory metaheuristic was developed which made use of the Tabu Search as an improvement procedure (ReAMTS) in order to solve the HFFVRP. The method was implemented and evaluated on two sets of test problems, which are used in the literature. In addition, its performance was compared with an exact method and a set of tractable instances. The computational results demonstrated high-quality results within a reasonable time.